Evidence on impacts of automated vehicles on traffic flow efficiency and emissions: Systematic review

被引:10
作者
Aittoniemi, Elina [1 ]
机构
[1] VTT Tech Res Ctr Finland Ltd, POB 1000, Espoo, Finland
基金
欧盟地平线“2020”;
关键词
ADAPTIVE CRUISE CONTROL; GENERIC MULTILEVEL FRAMEWORK; CAR-FOLLOWING MODELS; BEHAVIOR CHARACTERISTICS; DRIVER BEHAVIOR; SIMULATION; DEPLOYMENT;
D O I
10.1049/itr2.12219
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Despite high expectations of driving automation improving road traffic, its practical implications on traffic flow and emissions are not yet definite. This study systematically reviewed literature on practical impacts of non-connected automation of passenger cars on motorway traffic efficiency. A conceptual framework showed the importance of understanding interactions between vehicles, both human-driven and automated, but they are not yet sufficiently known and reproduced by traffic models. Field studies have focused on equipped vehicles. Simulation studies have used different models and assumptions, narrow fleet compositions and road layouts, and covered the theoretical potential in ideal conditions rather than likely impacts in practice. Simulations with automated vehicle time gaps below 1.2 s have found throughput increases, but recent field experiments and simulations using commercial ACC vehicles indicate decreased traffic flow efficiency with increasing traffic volumes and penetration rates. Concluding implications for real traffic from available data is challenging. While benefits are possible for equipped vehicles in low traffic, results suggest negative implications for throughput and emissions at higher traffic volumes. Importantly, more differentiated discussion on the impacts of automated vehicles on traffic flow is needed, considering also the practical implications, such as tradeoffs with safety goals, if benefits are to be achieved.
引用
收藏
页码:1306 / 1327
页数:22
相关论文
共 100 条
  • [91] Effects of adaptive cruise control systems on highway traffic flow capacity
    VanderWerf, J
    Shladover, SE
    Miller, MA
    Kourjanskaia, N
    [J]. INTELLIGENT TRANSPORTATION SYSTEMS AND VEHICLE-HIGHWAY AUTOMATION 2002: HIGHWAY OPERATIONS, CAPACITY, AND TRAFFIC CONTROL, 2002, (1800): : 78 - 84
  • [92] Adaptations in driver behaviour characteristics during control transitions from full-range Adaptive Cruise Control to manual driving: an on-road study
    Varotto, Silvia F.
    Farah, Haneen
    Bogenberger, Klaus
    van Arem, Bart
    Hoogendoorn, Serge P.
    [J]. TRANSPORTMETRICA A-TRANSPORT SCIENCE, 2020, 16 (03) : 776 - 806
  • [93] Empirical Longitudinal Driving Behavior in Authority Transitions Between Adaptive Cruise Control and Manual Driving
    Varotto, Silvia F.
    Hoogendoorn, Raymond G.
    van Arem, Bart
    Hoogendoorn, Serge P.
    [J]. TRANSPORTATION RESEARCH RECORD, 2015, (2489) : 105 - 114
  • [94] Viti F, 2008, IEEE INT VEH SYM, P444
  • [95] Help or hindrance? The travel, energy and carbon impacts of highly automated vehicles
    Wadud, Zia
    MacKenzie, Don
    Leiby, Paul
    [J]. TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE, 2016, 86 : 1 - 18
  • [96] Wood M, 2019, SAFETY 1 AUTOMATED D
  • [97] Automated vehicle-involved traffic flow studies: A survey of assumptions, models, speculations, and perspectives
    Yu, Haiyang
    Jiang, Rui
    He, Zhengbing
    Zheng, Zuduo
    Li, Li
    Liu, Runkun
    Chen, Xiqun
    [J]. TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2021, 127
  • [98] Recent developments and research needs in modeling lane changing
    Zheng, Zuduo
    [J]. TRANSPORTATION RESEARCH PART B-METHODOLOGICAL, 2014, 60 : 16 - 32
  • [99] Zhou A., 2021, ARXIV PREPRINT
  • [100] An Automated Vehicle Fuel Economy Benefits Evaluation Framework Using Real-World Travel and Traffic Data
    Zhu, Lei
    Gonder, Jeffrey
    Bjarkvik, Eric
    Pourabdollah, Mitra
    Lindenberg, Bjorn
    [J]. IEEE INTELLIGENT TRANSPORTATION SYSTEMS MAGAZINE, 2019, 11 (03) : 29 - 41